Learning dynamical systems from data: An introduction to physics-guided deep learning | PNAS
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Traditional physics-based models are first-principled, explainable, and sample-efficient. they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret introduce the framework of physics-guided DL with a spec
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- Traditional physics-based models are first-principled, explainable, and sample-efficient.
- they require a large amount of labeled training data. Furthermore, its predictions may disobey the governing physical laws and are difficult to interpret
- introduce the framework of physics-guided DL with a special emphasis on learning dynamical systems
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